An Increase in Synaptic NMDA Receptors in the Insular Cortex Contributes to Neuropathic Pain
Bibliographic record
Abstract
Neurons in the insular cortex are activated by acute and chronic pain, and inhibition of neuronal activity in the insular cortex has analgesic effects. We found that in a mouse model in which peripheral nerve injury leads to the development of neuropathic pain, the insular cortex showed changes in synaptic plasticity, which were associated with a long-term increase in the amount of synaptic N-methyl-d-aspartate receptors (NMDARs), but not that of extrasynaptic NMDARs. Activation of cyclic adenosine monophosphate (cAMP)-dependent signaling enhanced the amount of synaptic NMDARs in acutely isolated insular cortical slices and increased the surface localization of NMDARs in cultured cortical neurons. We found that the increase in the amount of NMDARs required phosphorylation of the NMDAR subunit GluN2B at Tyr(1472) by a pathway involving adenylyl cyclase subtype 1 (AC1), protein kinase A (PKA), and Src family kinases. Finally, injecting NMDAR or GluN2B-specific antagonists into the insular cortex reduced behavioral responses to normally nonnoxious stimuli in the mouse model of neuropathic pain. Our results suggest that activity-dependent plasticity takes place in the insular cortex after nerve injury and that inhibiting the increase in NMDAR function may help to prevent or treat neuropathic pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".